Multiple Sclerosis Prediction and Monitoring of Progression Study

NCT ID: NCT05685784

Last Updated: 2024-01-08

Basic Information

• Recruitment Status: RECRUITING
• Clinical Phase: NA
• Total Enrollment: 70 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2022-03-01
• Study Completion Date: 2024-09-30

Brief Summary

Multiple sclerosis (MS) is a auto-immune disease that is mostly characterized by acute clinical relapses and/or focal inflammation in the central nervous system (CNS) followed by recovery. Yet, a significant part of the patients also experience a progressive decline in function. This progressive phase usually has an insidious onset causing a delay for diagnosis and adjusted therapies. There are plenty of clinical assessments available to measure walking speed, cognition, sleep,.... . But these assessments are merely a snapshot of the patient 's symptoms. By monitoring these parameters at home, real life data can be provided to capture subclinical signs of progression. The goal of this study is to detect a digital biomarker for progressive MS at an earlier stage next to validating wearables by comparing them to golden standard measurements such a polysomnography or gait analysis in a specialized lab.

Detailed Description

Background:

Multiple sclerosis (MS) is the most common cause of non-traumatic neurological disability in young adults leading to an important personal and socio-economic burden. From a pathophysiological point of view MS is considered to be an autoimmune disease in which the immune system mistakenly attacks the central nervous system (CNS). MS is usually devided into three clinical phases. Most people with MS experience sudden relapses followed by a remitting periode (RRMS). Fot this type of MS, the therapeutic landscape has evolved extensively over the last decade. Unfortunately, a significant part of the patients still experience progressive decline in function despite not experiencing discrete clinical relapses. The progressive MS phenotype can be divided in two subtypes known as SPMS and primary progressive MS (PPMS) dependent on preceding RRMS or not. A variety of clinical measures has enabled us to compose a valid follow-up of the disease course, yet they do not evaluate outpatient or long-term monitoring and they also lack sensitivity for early detection of disability progression. Up-to-date, there is no clear consensus on how to diagnose SPMS and it remains difficult to define when a patient enters the progressive phase as the diagnosis is usually made retrospectively. Implementing digital biomarkers would potentially provide us with a more realistic and more sensitive view of the progressive evolution in different spheres of functioning. This also counts for autonomic dysfunction and sleeping disorders, where no standardized monitoring is available for MS. Using wearables to capture the digital biomarkers could fill the gap of knowledge in evaluating, monitoring and predicting disability progression in MS. to this day there is no precise biomarker or composite tool that can differentiate the MS phenotypes or help us initiate/adjust therapy earlier on in progression. Introducing wearable's that could collect basic clinical parameters on a day-to-day basis would potentially give researchers a more realistic and more sensitive insight of the general course of the disease.

Rationale:

Evolution in machine learning enables unbiased detection of biomarkers encoded in different biosignal modalities. The ability to track MS disease-related physiological and behavioral signals over longer periods of time on an outpatient basis serves the unmet need of early diagnosis and adequate monitoring of (relapse independent) disease progression. This has major clinical implications since biomonitoring could be a critical tool for MS care practitioners in patient-centered multidisciplinary care.

Study design:

This is an open-label, monocentric diagnostic study where the investigators will test the feasibility and validity (as compared to golden standard measures) of wearables, provided by Byteflies, in adequate extended outpatient evaluation and monitoring of PwMS. The investigators will further evaluate how these biosignals correlate with conventional outcome measures at their primary visit to evaluate the prognostic potential of wearable monitoring

Conditions

Progressive Multiple Sclerosis

Study Design

• Allocation Method: NON_RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: DIAGNOSTIC
• Blinding Strategy: NONE

Study Groups

Healthy volunteer

• 20 Healthy volunteers required for gait measurement: Standard gait analysis whilst simultaneously wearing the investigational sensor dots
• 15 Non-MS patients with an indication for polysomnography (PSG): Standard PSG whilst simultaneously wearing the investigational sensor dots

Group Type: EXPERIMENTAL

Bytelfies kit - sensor dot

Intervention Type: DEVICE

Participants will be asked to undergo a standard of care gait analysis and PSG whilst simultaneously wearing sensor dots.

GAIT: sensor dots will be placed in the neck, on the chest and one on both ankles.

PSG: sensor dots will be placed on the forehead, chin, chest, abdomen, both legs(tibialis anterior) and an SpO2 device will be placed on the finger middle finger of the non-dominant hand

People with MS

• 20 patients with MS required for gait measurement: Standard gait analysis whilst simultaneously wearing the investigational sensor dots
• 15 MS patients with an indication for polysomnography (PSG): Standard PSG whilst simultaneously wearing the investigational sensor dots

Group Type: EXPERIMENTAL

Bytelfies kit - sensor dot

Intervention Type: DEVICE

Participants will be asked to undergo a standard of care gait analysis and PSG whilst simultaneously wearing sensor dots.

GAIT: sensor dots will be placed in the neck, on the chest and one on both ankles.

PSG: sensor dots will be placed on the forehead, chin, chest, abdomen, both legs(tibialis anterior) and an SpO2 device will be placed on the finger middle finger of the non-dominant hand

Interventions

Bytelfies kit - sensor dot

Participants will be asked to undergo a standard of care gait analysis and PSG whilst simultaneously wearing sensor dots.

GAIT: sensor dots will be placed in the neck, on the chest and one on both ankles.

PSG: sensor dots will be placed on the forehead, chin, chest, abdomen, both legs(tibialis anterior) and an SpO2 device will be placed on the finger middle finger of the non-dominant hand

Intervention Type: DEVICE

Other Intervention Names

Gait analysis validation; PSG validation

Eligibility Criteria

Inclusion Criteria

• Relapsing Remitting (RR) or Primary Progressive (PPMS) MS as defined by 2017 Mc Donald criteria, or Secondary Progressive (SPMS) according to Lorscheider criteria AND having an EDSS ≤ 6.5
• Healthy control
• Non-MS Patient with an indication for polysomnography
• Age 18-60 years inclusive

Exclusion Criteria

• Patients who were prescribed 4-aminopyridin during the last 30 days.
• Patients with severe cardiac, pneumological, neurological, hematological, immunological, infectious, rheumatoid, endocrinological, gastro-intestinal, urological comorbidity that may interfere with outcome measures as determined by the investigators.
• Confirmed clinical relapses or new lesions on MRI during the last six months
• Known allergy to electrodes used as part of the study protocol
• Having an implanted device, such as (but not limited to) a pacemaker, cardioverter defibrillator (ICD), and/or neural stimulation device.

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 60 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

University Ghent

OTHER

Sponsor Role: collaborator

Byteflies

INDUSTRY

Sponsor Role: collaborator

University Hospital, Ghent

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Guy Laureys, MD, PhD

Role: PRINCIPAL_INVESTIGATOR

University Hospital, Ghent

Locations

University Hospital Ghent

Ghent, Oost-Vlaanderen, Belgium

Site Status: RECRUITING

Countries

Belgium

Central Contacts

Liesbeth Van Hijfte, Master

Role: CONTACT

liesbeth.vanhijfte@uzgent.be

+3293321168

Cathérine Dekeyser, MD

Role: CONTACT

catherine.dekeyser@uzgent.be

+32 9 33 25609

Facility Contacts

Liesbeth Van Hijfte, M.Sc.

Role: primary

liesbeth.vanhijfte@uzgent.be

+3293321168

Guy Laureys, MD, PhD

Role: backup

guy.laureys@uzgent.be

Other Identifiers

CIV-BE-20-09-034669

Identifier Type: OTHER

Identifier Source: secondary_id

BC-07811

Identifier Type: -

Identifier Source: org_study_id